At a Glance
- Tasks: Join us as a Quantitative Finance Intern, working on trading strategies and data analysis.
- Company: Morgan Stanley is a global leader in investment banking and financial services.
- Benefits: Enjoy comprehensive employee perks, including support for work-life balance and career growth.
- Why this job: Be part of an innovative team that values diversity and empowers your creativity.
- Qualifications: Pursuing a Master or PhD in relevant fields with programming skills in Python or similar languages.
- Other info: Coding assessment may be required; apply with CV and Cover Letter in English.
What will you do
Strategists typically work very closely with desks across business lines, are commercially driven and revenue focussed. The below four profiles describe the different categories of roles available within Strats. In many cases an individual role will encompass aspects of each.- Electronic Trading Strategists are financial and software engineers focus on clients who use our Algorithmic Trading suite. The goal is to advise, optimize and reduce the cost of execution.  You will become familiar with the design and implementation of our algorithmic suite and help shape it’s evolution.  The Strategists are client facing, so adaptability, personality and collaborative interpersonal skills are important
- Desk Strategists use statistical techniques and machine learning to develop and optimise trading strategies, tools, components and flows. Working closely with Electronic Trading Strategists and trading desks, they apply rigorous quantitative research and portfolio construction techniques to design systematic trading strategies and models.
- Modelling Strategists use applied probability and numerical analysis to create pricing models and hedging strategies that drive trading decisions. Working closely with trading desks, they enhance Morgan Stanley's ability to trade innovative products and improve the management of the Firm’s trading risk.
- Data Strategists use advanced big data, machine learning and AI techniques to facilitate data usage, analysis and commercialisation. Closely work with trading desk and technology to develop cutting edge innovative ways to improve data infrastructure, quality and control.
Qualifications
- You have or are studying towards a Master or PhD level degree and have graduated in 2025 or graduating in 2026
- You have a background in mathematics, statistics, engineering, computer science, or related field in an academic setting
- You have knowledge of Python, Scala, Java, KDB/q, C++, or similar programming language
- You have a keen interest in the financial markets and the drive and desire to work in a fast-paced, team-oriented environment
- Curiosity, creativity, willingness to bring new ideas to the table, and approach problems differently
- Pragmatic approach to ensuring delivery on a timely basis
- You will possess practical problem-solving skills with a great attention to detail
- You are able to communicate effectively in both written and verbal English
- Please only submit a CV and Covering Letter in English only as part of your application
- You may be required to do a coding assessment as part of your application (you will be notified if this is required)
Why this job
We have a track record of innovation and passion for unlocking new opportunities, we help our clients raise, manage and allocate capital. We do this by offering a wide range of investment banking, securities, wealth management and asset management services. All that we do at Morgan Stanley is driven by our five core values: do the right thing, put clients first, lead with exceptional ideas, commit to diversity and inclusion, and give back. These aren’t just beliefs, they guide the decisions we make every day, ensuring we do what's best for our clients, communities and more than 80,000 employees around the world. And at the core of our success are the people who drive it - relentless collaborators and creative thinkers who are fuelled by diverse thinking and experiences. Wherever you are in our 1,200 global offices, you’ll have the opportunity to work alongside the best and the brightest in an environment where you are empowered to achieve your full potential. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.2026 Quantitative Finance Off-Cycle Internship (London) employer: Morgan Stanley

Contact Detail:
Morgan Stanley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land 2026 Quantitative Finance Off-Cycle Internship (London)
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative finance and algorithmic trading. Understanding current market dynamics and how they influence trading strategies will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Brush up on your programming skills, especially in Python or C++. Consider working on personal projects or contributing to open-source projects that showcase your coding abilities and understanding of financial models.
✨Tip Number 3
Network with professionals in the industry through platforms like LinkedIn. Attend finance-related events or webinars to connect with potential mentors who can provide insights into the role and the company culture at Morgan Stanley.
✨Tip Number 4
Prepare for potential coding assessments by practising common algorithms and data structures. Websites like LeetCode or HackerRank can be great resources to sharpen your problem-solving skills in a timed environment.
We think you need these skills to ace 2026 Quantitative Finance Off-Cycle Internship (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that align with the role of a Quantitative Finance Intern. Emphasise your background in mathematics, statistics, or programming languages like Python or C++.
Craft a Compelling Cover Letter: Your cover letter should reflect your passion for finance and your understanding of the role. Discuss your academic achievements, any relevant projects, and how your skills can contribute to the team at Morgan Stanley.
Showcase Problem-Solving Skills: In both your CV and cover letter, provide examples of how you've approached complex problems in the past. Highlight your attention to detail and your ability to deliver results in a timely manner.
Prepare for Coding Assessments: If you're notified about a coding assessment, brush up on your programming skills. Practice coding problems related to algorithms and data structures, as these are often key components of such assessments.
How to prepare for a job interview at Morgan Stanley
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in programming languages like Python, Scala, or C++. Be prepared to discuss any relevant projects or coursework that demonstrate your technical abilities, as this role requires a strong foundation in quantitative analysis and software engineering.
✨Demonstrate Your Interest in Financial Markets
Express your passion for the financial markets during the interview. Discuss any recent trends or news that have caught your attention, and be ready to explain how they relate to the role you're applying for. This shows that you are not only qualified but also genuinely interested in the field.
✨Prepare for Problem-Solving Questions
Expect to face problem-solving scenarios or case studies during the interview. Practice articulating your thought process clearly and logically, as this will showcase your analytical skills and ability to approach complex problems pragmatically.
✨Emphasise Collaboration and Communication Skills
Since the role involves working closely with various teams, it's crucial to highlight your interpersonal skills. Share examples of past experiences where you successfully collaborated with others, and demonstrate your ability to communicate effectively, both verbally and in writing.